Data integration and high dimensional statistics in Medical Imaging

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Guest Editor
Dr. Laurent Risser
CNRS, Toulouse Mathematics Institute (UMR 5219), Univ Toulouse 3, F-31400 Toulouse, France.
Email: lrisser@math.univ-toulouse.fr

Manuscript Topics
Recent developments of Medical Imaging have deeply changed different fields the medical practice and more generally of Medical Science. Medical images indeed give the opportunity to observe physiological phenomena and pathologies which, not earlier than ten years ago, could only be seen using costly and invasive procedures. Image resolution has become increasingly finer, multi-modal image acquisition is now daily routine for clinical diagnosis, tracers are more and more efficient and large databases were defined to characterize major diseases. Most of the time, medical images are also related to other data such as e.g. gene expression or patient information. The massive amount of data generated by these images opens new questions in mathematical science, many of them being still widely opened. This special issue will focus on strategies to treat and to analyze such high dimensional and multi-modal datasets. An emphasis will be given to how mathematical and algorithmic strategies are applied to treat physiologically meaningful data. Related topics are multi-modal data integration, mathematical modeling, high dimensional statistics, statistical learning, and treatment of big data. Also of interest are the papers dealing with image registration, atlas creation, image segmentation, epidemiology, biostatistics, experimental planning. Application of the strategies to clinical or preclinical datasets, as well as large databases of medical data will be strongly appreciated.

Keywords: Medical imaging; multi-modality; data integration; high dimensional statistics; statistical learning; big data; biostatistics; image analysis.

Paper submission
All manuscripts will be peer-reviewed before their acceptance for publication.
The deadline for manuscript submission is 30 May 2015.

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